The SSL-based HSIC techniques are briefly summarized in [1]}, where authors also made a detailed comparison of these methods. The method presented in [2]} used pseudo or cluster-labeled samples to pre-train a CRNN for HSIC and small-sized labeled data is used to fine-tune the network. Similarly, [3]} proposed a semi-supervised HSIC framework that exploits PCA and extended morphological attribute profiles to extract pseudo-labeled samples which are fed to a CNN-based deep feature fusion network.
